Uma Arumugam, MD

	Although we have made several strides in clinical drug development, there are still several factors that impact our 

drug development endeavours as posited in the past. However, the encouraging news is that the probability of success (POS) in clinical drug development is higher than previously estimated. This is welcome news for investors and drug developers reaffirming their confidence in the return on their investment, specifically for ventures that bootstrap in order to increase the POS, given that they have limited human and capital resources.

	In particular, we have had tremendous innovation in clinical trial design methodologies in the last decade, especially with the introduction of adaptive trial design and master protocols (umbrella trials, basket trials, and platform trials). These, along with advancements made in the execution of these clinical trials with the use of technology (electronic data capture, electronic health records, and digitization), have paved the way for more efficient processes to be implemented and help us realize the benefits much more rapidly. However, with clinical trials becoming more complex, increasingly resource and capital intense, and time-consuming, there still lingers the question on the outcome of these trials in terms of success, despite our best efforts. For example, in oncology, it is well recognized that more than 95% of the drugs/compounds that have a demonstrable effect on animals, fail in Phase I clinical trials in humans, indicating that most preclinical models of cancer are inadequate. In addition, most of the anticancer drugs either have no effect on the overall survival of the cancer patient or may provide an increase in few months in overall survival. This dismal rate of success leads to the lingering question of the POS that every investor and drug developer would like to know prior to developing a portfolio of assets or a particular compound for a specific therapeutic indication.

	Estimates of POS in clinical trials have been published in the past with some variances in their approach and results (see 

). Last April, Chi Heem Wong and others at MIT published a revised 

 by reconstructing drug development pathways, which is believed to be a more accurate estimate of the POS in drug development. One of the interesting findings is that they obtained higher POS estimates for all phases relative to the estimates published before. Additionally, it has been shown to result in a lower estimated drug development cost, especially in Phase III, where the cost of conducting a trial dominates those of other phases.

A closer inspection of this data reveals an increasing trend post-2013, which was preceded by a decade of decrease in successful outcomes. This has mainly been attributed to careful licensing of compounds and better identifying potential failures, thus leading to higher productivity. They also propose two other possible reasons for the trend: one, the increased use of biomarkers to target drugs at patients who are more likely to produce a positive response; the other, the new wave of medical breakthroughs. They also found that clinical trials using biomarkers for patient stratification have higher success rates, especially in the area of oncology.

	Analyzing and interrogating both the scientific and operational data in order to assess the POS from all the accumulating clinical trials in an ongoing fashion will likely yield significant insights. Undertaking an assessment of the POS of an asset can be coupled with the product profile and safety assessments of assets/compounds prior to launching a clinical trial. As we make progress and gain additional actionable intelligence, we can perhaps develop a framework that can eventually be used as a guidance tool for designing clinical trials. Obviously, this will require resources to be allocated, which in the long term will have a profound impact on streamlining the process and, most importantly, reducing the cost of drug development.

MD, is Director, Clinical R&D, Early Phase Services, ICON plc

Articles

Undertaking an assessment of the POS can be coupled with the product profile and safety assessments of compounds prior to launching a clinical trial.

Predicting the Probability of Success in Clinical Drug Development

	Over the years, there has been a lot of debate surrounding the new drug approval process, specifically how very few drugs are being approved and the impact it has on patients’ lives. However, both as a keen observer and a critical contributor within the drug development industry, I am encouraged by the number of new drug approvals that were secured in 2017 alongside some notable “firsts”.     

	Below is a snap shot of all the approvals that were secured in 2017:

	o To put this in perspective, in the ten-year period from 2008 through 2016, the average was 31 novel drug approvals per year, with 

Of these 46 novel drugs, 15 (33%) were First-in-Class

	o Notable novel first-in-class approvals for 2017 include: Dupixent (dupilumab) to treat adults with moderate-to-severe eczema (atopic dermatitis), and Ocrevus (ocrelizumab) to treat adults with relapsing forms of multiple sclerosis and primary progressive multiple sclerosis.

Of these 46 novel drugs, 18 (39%) were approved to treat rare or “orphan” diseases that affect 200,000 or fewer Americans

	o Examples of drugs that advance the care of patients with rare diseases approved in 2017 include:

	a) Brineura (cerliponase alfa), a treatment for a specific form of Batten disease, a rare disease that can cause progressive neurological impairments, including seizures, visual problems/blindness, personality and behavior changes, dementia, and loss of the ability to walk, talk, and communicate, and

	b) Hemlibra (emicizumab), for the prevention of bleeding or to reduce the frequency of bleeding episodes in patients with hemophilia A who have developed antibodies called Factor VIII inhibitors. This is the first non-blood product approved for this condition.

Of these 46 novel drugs, 18 (39%) were designated as Fast Track. 

Fast Track speeds new drug development and review, for instance, by increasing the level of communication between FDA and drug developers, and by enabling FDA to review portions of a drug application ahead of the submission of the complete application.

Of these 46 novel drugs, 17 (37%) were designated as Breakthrough Therapies.

 A breakthrough therapy designation includes all the Fast Track program features, as well as more intensive FDA guidance on an efficient drug development program. Breakthrough therapy designation is designed to help shorten the development time of a potential new therapy.

Of these novel 46 drugs, 28 (61%) were designated Priority Review

. A drug receives a Priority Review if FDA determines that the drug could potentially provide a significant advance in medical care. The drug is reviewed within six months instead of the standard 10 months.

Of these 46 novel drugs, 6 (13%) were under the Accelerated Approval program.

 The application of accelerated approval brings drugs that can provide important advances to patients sooner than with traditional approvals.

Of these 46 novel drugs, 28 (61%) were designated in one or more expedited categories of Fast Track, Breakthrough, Priority Review, and/or Accelerated Approval.

Of these 46 novel drugs, 39 (85%) were approved on the “first cycle” of review, meaning without requests for additional information that would delay approval and lead to another cycle of review.

 From 2011 through 2016, FDA approved 204 novel drugs, of which 166 (81%) were approved on the first cycle. The rate for 2017 is consistent with this average. This helps to assure that the application contains the information FDA needs to be able to fully review-and if appropriate-approve an application.

Approval in the United States Before Other Countries

	o Although regulatory processes differ widely between FDA and those of regulatory agencies in other countries, 

36 of the 46 novel drugs approved in 2017 (78%) were approved in the United States before receiving approval in any other country.

	o Additionally, there were a total of 14 approvals of already-FDA-approved drugs that were accompanied by new data demonstrating safety and effectiveness of the same product for an additional purpose or for use in a different population of patients. Applications to modify the use of an already-approved drug or to expand its use to other patients are in a category of supplemental applications known as “efficacy supplements.” Notable among them was

	§ Keytruda (pembrolizumab), originally approved in 2014 to treat patients with advanced or unresectable melanoma who are no longer responding to other drugs. Throughout 2014 - 2017, it was approved for many new uses to treat patients with various forms of cancer. In May 2017, Keytruda was approved to treat patients whose cancers have a specific genetic feature (biomarker). 

This was the first time FDA has approved a cancer treatment based on a common biomarker rather than the location in the body where the tumor originated.

 It was additionally approved in 2017 to include treatment of patients with refractory classical Hodgkin lymphoma, a particularly difficult-to-treat type of Hodgkin lymphoma in which the cancer returns after treatment. It was also approved to treat certain patients with recurrent, locally advanced or metastatic forms of stomach cancer called gastric or gastro-esophageal junction adenocarcinoma.

3 already approved drugs were approved in 2017 by the FDA for use in expanded population of patients.

	· Abilify MyCite (aripiprazole tablets with sensor). Abilify was first approved by FDA in 2002, in tablet form, to treat patients with schizophrenia. It was subsequently approved to treat certain patients with bipolar I disorder and as adjunctive treatment of major depressive disorder. 

In 2017, Abilify MyCite was approved as the first tablet with an electronic sensor allowing patients to track the ingested medication via a smartphone or the cloud. Patients can also provide their caregivers or physician access to their information through a web-based portal.

Endari (L-glutamine oral powder), the first treatment approved for patients with sickle cell disease in almost 20 years.

 Prior to this approval, L-glutamine was approved as a prescription drug in 2004 to treat certain patients with short bowel syndrome.

	· Juluca (rilpivirine and dolutegravir), a combination of two FDA-approved drugs, each used in the treatment of certain patients with HIV. It was approved in 2017 as a complete regimen for the treatment of certain adults with HIV-1 infection. 

This is the first complete regimen containing only two HIV-1 drugs and neither is a nucleoside reverse transcriptase inhibitor (NRTI). 

	These new drug approval numbers for 2017 are certainly impressive, providing all of us engaged in drug development, and the health care industry as a whole, a sense of pride and encouragement regarding our accomplishments. But beyond these numbers, we have also made huge strides in our understanding and application of biomarkers and integrating technology (sensors) in drug development. These innovative approaches along with increased adoption of “seamless clinical trials” wherein combining two or more phases into one adaptive design study, I believe will continue to yield these encouraging numbers of new drug approvals hopefully in this current year and also in the years following.

, MD, Director, Clinical R&D, Early Phase Services at ICON Plc.

		https://www.fda.gov/Drugs/DevelopmentApprovalProcess/DrugInnovation/ucm537040.htm

An overview of all the drug approvals that were secured in 2017.

An Encouraging Snap Shot of New Drug Approvals by FDA in 2017

	Years ago, before entering medical school and embarking on my journey to become a full-fledged medical doctor, I had the privilege to take flying lessons. As a prerequisite, I was asked to review and have a sound comprehension of “Aeronautical Decision Making” (ADM). ADM entails what is called the “3P Model” of Perceive, Process and Perform. This mental exercise of gathering information, analyzing the information and arriving at decisions based on them, is crucial for the success of a flight. Fast forward, now, with the advent of process driven precision medicine, I cannot help but be reminded of the knowledge I had gained during my time at the flying school. I believe clinical drug development as a whole has matured to a point that to me reminds me of the process driven decision making akin to ADM.

 that was undertaken by Dr. Kohane and colleagues,

	achieved through an international network of clinical research collaborators spanning several continents around the globe has successfully demonstrated to us the significance of process driven approaches in medicine. Now, with the marriage of medicine and technology, doctors are able to better “perceive” all the disparate sources of complex information and “process” them enabling them to optimally “perform” their actions. This ability to diagnose disease pathologies, in the past, was a solo exercise based on very limited information made available to doctors.  With these new generations of technology embedded in today’s world of medicine, the art of decision making for us doctors has become more refined complementing our diagnoses and care delivery. An incidental, unintended yet positive consequence of this is a new wave of path breaking doctors who are extremely comfortable in tapping into technology that was not at their disposal years ago.

 that was conducted at 23 cancer centers around the world including Memorial Sloan Kettering Cancer Center, New York, and 

 is a testament to the application of converging data and its application in precision medicine. As evidenced from the results of this trial, the ability to precisely target the oncogene (BRAF V600 mutated cancers), based on genomic data is a prime example of how far we have come along in this arduous journey of clinical drug development, all along, fine tuning the process of decision making at every step of the way. This commendable feat, achieved through a lot of medical perseverance, is indeed a proud moment in the history of drug development and will be carved out as a historical milestone in drug development. Thus, this remarkable accomplishment gives me the pleasure of reminiscing my days of flying lessons, with the hope that there is many more exciting endeavors to come on the precision medicine front for the betterment of patients.

The recent landmark international trial that was conducted at 23 cancer centers around the world including Memorial Sloan Kettering Cancer Center, New York, had results published last month.

Recent Basket Trial Success Points to Precision Medicine

	One of the primal questions clinical trialists engaged in clinical research and development always face is do we “keep or kill” a drug based on the data in hand, specifically when we are left with the decision of whether to pursue an asset or not at the end of a Phase II trial.

	Key approaches in reducing Phase III attrition include a better target selection (selection of more validated and druggable targets) and routine pursuit of early POC studies in the clinic, especially in Phase I, for which biomarkers and surrogate endpoints can often be employed¹. A robust early phase trial design will help lay the groundwork for a successful Phase III. A Phase III trial may not be even warranted after a successful Phase II² for certain indications provided all the appropriate questions are asked and answered through a clinically sound Phase II trial design.

	The robustness of historical data and their application in a clinical trial design especially when go and no go decision is based on these trials are not only critical but extremely valuable. However, there appears to be a gap that exists. This gap can be addressed fairly easily. For example, in oncology trials we always look for “null” and “alternative” response rates of an outcome like the tumor response when studying an agent. As null responses require us to understand the historical data, it is critical that they become an integral part of a study design. Disappointingly, that always is not the case.

	One of the very first reviews, exploring the utility of historical data in go and no go decisions was published in the 

³. Based on their conclusion, many of the Phase II trials require historical data to determine null response rates but very few did so appropriately and those that did not concluded that the experimental regimen was worth studying further. Of the 134 qualifying trials (out of the 251 that were chosen for this review), 70 (52%) of the trials required historical data for study design. However, 32 (46%) of these trials did not cite the source of the historical data used and only 9 (13%) of the trials had clearly provided a single estimate as a rationale for the null based on historical data. Trials that did not cite historical data appropriately were significantly more likely to declare an agent to be active (82% versus 33%). Therefore, careful consideration should be given to historical data and their relevance when designing clinical trials especially while testing compounds in oncology.

	In 2014, ASCOâ´ undertook an exercise convening working groups for improving the design of future clinical trials yielding results that are clinically meaningful in patients (significantly improving survival, quality of life (QOL) or both). One of the key outcomes from this exercise was that patient symptoms from cancer progression and tolerance to treatment related toxicities were critical when considering whether a new treatment produces a clinically meaningful outcome. For example, a less toxic compound with negligible increase in efficacy is acceptable whereas conversely a highly toxic compound need to have established a substantial increase in efficacy to be clinically meaningful for patients. Overall, there seems to have been a consensus that overall survival will continue to serve as the primary measure of clinically meaningful outcome while the value of progression free survival and other surrogate end points as valid end points may need to be applied in certain clinical situations.

	As such, appropriately utilizing historical data and employing clinically meaningful outcomes in a clinical trial design can help improve the quality of data and potentially address this attrition. Although these are not all encompassing strategies or solutions, these measures will result in generating trial data that is more robust and evidence based eventually helping us within clinical research and development in the go and no go decision making process.  So I encourage, as clincial trialists engaged in clinical research and development, we begin not only to explore but also begin to adopt strategies and design considerations including the aforementioned in practice, while continually looking for ways and means of further optimizing “go and no go decisions”.

http://www.nature.com/nrd/journal/v9/n3/full/nrd3078.html

http://www.nature.com/nrclinonc/journal/v9/n4/full/nrclinonc.2011.190.html

http://clincancerres.aacrjournals.org/content/13/3/972.full?sid=66e94f29-2e4a-435f-b93c-6babd0f3ae68

http://jco.ascopubs.org/content/32/12/1277

One of the primal questions clinical trialists engaged in clinical research and development always face is do we “keep or kill” a drug based on the data in hand.

Go and No Go Decisions – Optimizing Design Strategies

There are various estimates in the public domain, including one by McKinsey¹, that applying big data strategies could potentially generate up to $100 billion in value annually across the US healthcare systems, specifically by optimizing innovation and improving the efficiency of research and clinical trials. A component of this “Big Data” is the data acquired during a clinical trial regardless of the phase (early or late phase).  A 

 that IBM’s Watson will help Mayo Clinic in identifying suitable patients for cancer trials, is indeed a strong indicator that the collaboration between doctors and technologists in pharmaceutical drug development has matured further.   

With the advent of global CROs entering into the capital intensive sector of healthcare reimbursements, supporting pharmaceutical and biotech companies to formulate their reimbursement strategy, it is only a natural course of evolution for them to be more data-driven and focused, thereby creating value for the drug product they are developing as early as they could. However, while doing so, the CROs should recognize that a “Patient’s Journey” begins as early as during the early phase of drug development, and encompasses several data-centric efforts from patient data visualization through to data mining in order to create robust data. To that end, there are several tools, technology platforms, and initiatives that are currently being explored, including the FDA’s $116 million pilot program called the “Mini-Sentinel,” established in 2008, that automatically combs medical databases for signs of drug safety issues that were not detected before approval. 

One such tool—among several others that I use frequently in my organization and have been fascinated with due to its sheer ease of use and value—is our own in-house data visualization tool. I have had the fortune to use this tool to learn more about our subjects and patients in early phase trials. This tool not only is user friendly (read doctor friendly as well) but also provides a quick and nearly a “real-time” glimpse into safety profiles, which in turn enables me to make evidence based decisions. Moreover, I am able to readily share this data and associated information with the sponsors who may then use that information accordingly to address the evolving safety or clinical trial design related issues. 

Most importantly, it provides me an insight into evolving data, highlighting trends, emerging signals, outliers, unusual patterns, and deviations in a clinical trial that otherwise may not be available to me until the end of the trial, and, even then, in less clear tables and listings that is critical for reviewers at the regulatory agencies. This proactive gathering of information about the behavior of a drug in development has proved to be very valuable. Such time-sensitive safety data, on several occasions, have been discovered during routine use of this data visualization tool, helping my medical colleagues at sponsor companies in their decisions as well.  

As medical doctors who are sworn by the Hippocratic Oath, we are always obligated to ensure the safety and welfare of patients participating in clinical trials. Thus, utilizing tools and technology towards achieving that obligation should be part and parcel of any clinical trial. However, the challenge my colleagues and I face is the shortcomings of several of these tools and technology platforms, besides tending to be a tad sophisticated for a medical doctor with limited technology knowledge.

Therefore, the tools and technology that doctors gravitate towards should attempt to fulfill the following criteria:

Ease of use: able to provide a user-friendly environment

Informative: able to quickly convey the information as facilitating data interpretation

Compatible with legacy systems: able to work with existing tools and technology

Integrating capabilities: able to receive data from disparate sources 

With drug recalls and safety being scrutinized more than ever before, we as an industry should embrace and encourage application of data visualization tools that enables doctors engaged in drug development, especially when “time is of the essence.” Since doctors have an integral and a valuable part to play in drug development, John F. Kennedy’ saying that “Man is still the most extraordinary computer of all,” is even more applicable in this environment. Therefore, doctors are critical to fulfill this void and serve as the conduit between data and drug development. Thus as doctors, we have an obligation to the millions of patients we directly and indirectly impact as a result of our decision making in espousing the application of tools and technology in drug development. This, I am sure, will result in better health outcomes there by decreasing the capital burden in our healthcare spending.

Uma Arumugam, MD, Director, Clinical Research & Development, Early Phase Services, ICON plc.

1.              McKinsey Global Institute – Big Data: The next frontier for innovation, competition and productivity

There are various estimates in the public domain that applying big data strategies could potentially generate up to $100 billion in value annually across the US healthcare systems.

Doctors, Data, and Drug Development

As I was trying out a series of corrective lenses at an optometrist last week to choose the one that finally provided me the clarity that I was looking for, it made me pose a profound question to myself about perception and reality. This made me cherish the quote “Reality is merely an illusion, albeit a very persistent one” by Albert Einstein, that I think fits well in our current day to day lives, be it personal or professional.

Being a clinical trialist engaged in drug development in the pharmaceutical industry, my inherent wave of thoughts then proceeded to my profession and our industry as whole. That is when I realized, that as an industry, how we have over the years become religiously skeptic in our perception and views about the Food and Drug Administration (FDA). To my dismay, this has been the general discourse both in the media and the industry, although there have been one too many occasions especially in the last few years where FDA through its promotion of innovation has evolved to become one of the most revered premier scientific institutions that it was set to be in the 1800s.  

Perhaps it is time for us to take a moment to view the accomplishments of the FDA with a different set of lenses and also celebrate our colleagues at the FDA who have contributed to its success. Under the stewardship of Dr. Margaret Hamburg, the agency appears to be flourishing scientifically mainly because some of her path-breaking, innovative initiatives and therefore, I believe it is time to recognize and give credit when and where it is due and applaud from the sidelines.

With the drug discovery and development timelines strained more than ever before, a call to action was placed by a panel at a Conference on Clinical Cancer Research in 2011, towards devising innovative pathways for expedited approval of drugs.¹

Courtesy of the American Association of Cancer Research 2011 Cancer Progress Report

Subsequently, FDA in order to expedite the drug approval process, collaborating with several external stake holders came up with a novel pathway called the “Breakthrough Therapy Designation” (BTD).  This is specifically tailored towards Sponsors seeking approval for a drug that treats a serious or life-threatening condition where the preliminary clinical evidence indicates that the drug may demonstrate substantial improvement on a clinically significant endpoint(s) over available therapies. Note, this in contrast to a fast track program for a drug that treats a serious or life-threatening condition, wherein nonclinical or clinical data demonstrate the potential to address unmet medical need.2 With collective support from the industry, researchers, and academia, Dr. Hamburg successfully led the collaborative effort on the Hill which eventually saw this novel ideal and her efforts behind the scenes, bear fruit.

In the spring of 2012, the bipartisan Advancing Breakthrough Therapies for Patients Act was introduced by Senators Michael Bennet (D-CO), Orrin Hatch (R-UT) and Richard Burr (R-NC) and Representatives Diana DeGette (D-CO) and Brian Bilbray (R-CA). President Obama signed this into a law as part of the FDASIA on July 9, 2012.  This was no mean feat to achieve, as Dr. Hamburg using her good offices and working with our elected representatives from both sides of the aisle was able to successfully have this bill enacted which led to Senators Tom Harkin (D-IA) and Michael Enzi (R-WY) releasing the following statement: “While people like to talk about polarization and gridlock in Washington, this bill is a victory for both bipartisanship and for the millions of American who rely on medicines and medical devices.”

The number of drugs to date that has been granted BTD status is a clear indicator that this novel program has indeed met its objectives since it successful launch.  Of course, the entire industry along with Main Street and Wall Street are closely watching this unfold, as we are yet to reap the economic benefits. Nevertheless, this phenomena has spurred innovation all around the globe including at the Department of Health, UK which is now implementing a similar program that is designed to offer patients access to novel medicines.4 With the initial response from all quarters very positive, my hope and optimism is that this novel program continues to expand, so millions of patients around the world receive access to medicines that otherwise would be unavailable simply because of lack of spirited innovation. 

This was made possible by the sheer determination, devotion and the visionary leadership of Dr. Hamburg and her colleagues at the FDA and so for that, I salute them.

http://www.fda.gov/regulatoryinformation/legislation/federalfooddrugandcosmeticactfdcact/significantamendmentstothefdcact/fdasia/ucm341027.htm

http://www.fda.gov/Drugs/DevelopmentApprovalProcess/HowDrugsareDevelopedandApproved/DrugandBiologicApprovalReports/INDActivityReports/ucm373559.htm

https://www.gov.uk/government/news/cutting-edge-drugs-to-be-fast-tracked-to-patients

As I was trying out a series of corrective lenses at an optometrist last week to choose the one that finally provided me the clarity that I was looking for, it made me pose a profound question to myself about perception and reality.